Laboratory of Structural Bioinformatics, Centre of New Technologies, University of Warsaw, Banacha 2c, 02-097 Warsaw, Poland; Laboratory of Bioinformatics, Nencki Institute of Experimental Biology, Pasteura 3, 02-093 Warsaw, Poland.
Laboratory of Bioinformatics, Nencki Institute of Experimental Biology, Pasteura 3, 02-093 Warsaw, Poland.
J Struct Biol. 2018 Jul;203(1):54-61. doi: 10.1016/j.jsb.2018.02.004. Epub 2018 Feb 14.
Computational protein design is a set of procedures for computing amino acid sequences that will fold into a specified structure. Rosetta Design, a commonly used software for protein design, allows for the effective identification of sequences compatible with a given backbone structure, while molecular dynamics (MD) simulations can thoroughly sample near-native conformations. We benchmarked a procedure in which Rosetta design is started on MD-derived structural ensembles and showed that such a combined approach generates 20-30% more diverse sequences than currently available methods with only a slight increase in computation time. Importantly, the increase in diversity is achieved without a loss in the quality of the designed sequences assessed by their resemblance to natural sequences. We demonstrate that the MD-based procedure is also applicable to de novo design tasks started from backbone structures without any sequence information. In addition, we implemented a protocol that can be used to assess the stability of designed models and to select the best candidates for experimental validation. In sum our results demonstrate that the MD ensemble-based flexible backbone design can be a viable method for protein design, especially for tasks that require a large pool of diverse sequences.
计算蛋白质设计是一组计算氨基酸序列的程序，这些序列将折叠成特定的结构。Rosetta Design 是一种常用的蛋白质设计软件，它允许有效地识别与给定骨架结构兼容的序列，而分子动力学 (MD) 模拟可以彻底地采样接近天然的构象。我们对一种在 MD 衍生的结构集合上启动 Rosetta 设计的方法进行了基准测试，结果表明，与目前仅使用少量计算时间的可用方法相比，这种组合方法生成的序列更加多样化，多样性增加了 20-30%。重要的是，在不损失设计序列质量的情况下实现了这种多样性的增加，通过评估它们与天然序列的相似性来衡量。我们证明，基于 MD 的方法也适用于从头开始设计任务，从没有任何序列信息的骨架结构开始。此外，我们实现了一种协议，可以用于评估设计模型的稳定性，并选择用于实验验证的最佳候选者。总之，我们的结果表明，基于 MD 集合的柔性骨架设计可能是一种可行的蛋白质设计方法，特别是对于需要大量多样化序列的任务。
